SYMP 10-4 - Integrating field and remote sensing data for landscape-level perspectives of animal impacts on carbon cycling

Wednesday, August 9, 2017: 9:40 AM
D135, Oregon Convention Center
Andrew B. Davies and Gregory P. Asner, Department of Global Ecology, Carnegie Institution for Science, Stanford, CA

Understanding the role of animals in the carbon cycle requires detailed and accurate measurements of animal contributions to carbon storage and exchange. However, to fully appreciate the extent of animal influence on global carbon cycling, detailed field measurements need to be correctly extrapolated to landscape scales in order to relate such animal contributions to geospatial analyses of carbon stocks. Remote sensing technology allows the surveying of large areas, and the estimation of above-ground carbon density (ACD) when combined with field-derived allometric equations. We demonstrate the potential of this approach by combining Light Detection and Ranging (LiDAR) with field-based allometry of savanna vegetation to measure variation in ACD in response to increasing, but spatially varied elephant densities in South Africa’s Kruger National Park. We surveyed the landscape biennially with airbourne LiDAR from 2008 to 2014, and analysed changes in ACD in relation to annual elephant census data and environmental drivers, including mean annual rainfall, elevation and fire return interval.


Landscape-scale changes in ACD closely matched patterns of elephant density, decreasing where elephant densities were high. However, such elephant-induced decreases in ACD were not uniform across the landscape, but interacted with key environmental factors, e.g. fire, that mediated the strength of elephant effects. Our results demonstrate the profound influence animals can have on carbon cycling across landscapes, and how this varies through space and time. Furthermore, we show how new insights can be uncovered when field data (e.g. allometric equations of woody biomass and animal census data) are combined with remote sensing to build a landscape-level perspective of variation in carbon storage and flux induced by animals.